药物信息学研究工作与成果

zouquan

研究方向

• 药物靶标预测
• 药物毒副作用预测
  

基金项目

• 面向药物副作用识别的多视角稀疏模型研究，62172076，面上，丁漪杰主持
• 基于多类特征整合与排序学习的药物-靶标相互作用预测，62101094，青年，茹晓青主持
• 基于单细胞测序数据的药物反应预测研究，62201129，青年，齐忍主持
  

研究成员

• 邹权（电子科技大学，教授）
• 鱼亮（西安电子科技大学，教授）
• 苏苒（天津大学，教授）
• 丁漪杰（电子科技大学长三角研究院（衢州），研究员）
• 张鑫（电子科技大学长三角研究院（衢州），博士后）
• 齐忍（电子科技大学长三角研究院（衢州），博士后）
• Stalin Antony（电子科技大学，博士后）
• 茹晓青（电子科技大学长三角研究院（衢州），实验员、科研助理）
• 任忠豪（湖南大学，博士生）
  

发表论文

• Shunyun Yang, Runxin Guo,Rui Liu, Xiangke Liao, Quan Zou*,Benyun Shi*, Shaoliang Peng*. cmFSM: A Scalable CPU-MIC CoordinatedDrug-Finding Tool by Frequent Subgraph Mining. BMC Bioinformatics.2018, 19(Suppl4): 98 (codes)
• Ran Su, Xinyi Liu, LeyiWei, Quan Zou*. Deep-Resp-Forest: Adeep forest model to predict anti-cancer drug response. Methods. 2019, 166: 91-102
• Xiaoqing Ru, Lida Wang*,Lihong Li, Hui Ding, Xiucai Ye, Quan Zou*.Exploration of the Correlation between GPCRs and Drugs Based on a Learning toRank Algorithm. Computers in Biology andMedicine. 2020, 119: 103660
• LiangYu, Yayong Shi, Quan Zou, ShuhangWang, Liping Zheng, Lin Gao. Exploring drug treatment patterns based on theaction of drug and multilayer network model. International Journal of Molecular Sciences. 2020, 21: 5014
• YifangShi, Lin Gao, Quan Zou, Liang Yu. Prediction of drug-target interactionsbased on multi-layer network representation learning. Neurocomputing.2021, 434: 80-89
• Xiaoqing Ru, Xiucai Ye*, Tetsuya Sakurai, Quan Zou, Lei Xu, ChenLin*. Current status and future prospects of drug-target interactionprediction. Briefings in FunctionalGenomics. 2021, 20(5):312-322
• Yuxin Gong, Bo Liao*, Peng Wang, Quan Zou. DrugHybrid_BS: Using Hybrid Feature Combined With Bagging-SVM to Predict Potentially Druggable Proteins. Frontiers in Pharmacology. 2021, 12: 771808
• YuCheng, Yongshun Gong, Yuansheng Liu*, Bosheng Song*, Quan Zou. Molecular design in drug discovery: a comprehensivereview of deep generative models. Briefingsin Bioinformatics. 2021, 22(6):bbab34.
• Yijie Ding, Jijun Tang,Fei Guo*, Quan Zou*. Identification of drug-target interactions viamultiple kernel-based triple collaborative matrix factorization. Briefingsin Bioinformatics. 2022, 23(2): bbab582 (data and codes)
• Xiaoqing Ru, Xiucai Ye*,Tetsuya Sakurai, Quan Zou*. NerLTR-DTA: Drug-target binding affinityprediction based on neighbor relationship and learning to rank. Bioinformatics.2022, 38(7): 1964-1971. (codes and datasets)
• Ran Su, Haitang Yang, Leyi Wei*, Siqi Chen*, Quan Zou*. A multi-label learning model for predicting drug-induced pathology in multi-organ based on toxicogenomics data. PLoS Computational Biology. 2022, 18(9): e1010402. (codes)
• Yuqing Qian, Yijie Ding*, Quan Zou*, Fei Guo*. Identification ofdrug-side effect association via restricted Boltzmann machines with penalizedterm. Briefings in Bioinformatics. Doi: 10.1093/bib/bbac458
• Zhonghao Ren, ZhuhongYou*, Quan Zou*, Changqing Yu*, Yanfang Ma*, Yongjian Guan, Hairu You, XinfeiWang, Jie Pan. DeepMPF: deep learning framework for predicting drug–target interactions based on multi-modal representation with meta-path semanticanalysis. Journal of Translational Medicine. 2023, 21: 48 (web server)
• Hongjie Wu, Junkai Liu,Tengsheng Jiang, Quan Zou, Shujie Qi, Zhiming Cui, Prayag Tiwari*, YijieDing*. AttentionMGT-DTA: A multi-modal drug-targetaffinity prediction using graph transformer and attention mechanism. NeuralNetworks. 2024, 169: 623-636  (codes)
• Chao Pang, Jianbo Qiao,Xiangxiang Zeng, Quan Zou, LeyiWei*. Deep Generative Models in De Novo Drug Molecule Generation. Journal of Chemical Information andModeling. Doi: 10.1021/acs.jcim.3c01496
• Yijie Ding, Fei Guo,Prayag Tiwari, Quan Zou. Identification of Drug-Side Effect AssociationVia Multi-View Semi-Supervised Sparse Model. IEEE Transactions on ArtificialIntelligence. DOI: 10.1109/TAI.2023.3314405
• Yijie Ding, HongmeiZhou, Quan Zou*, Lei Yuan*. Identification of Drug-side EffectAssociation via Correntropy-loss based Matrix Factorization with Neural TangentKernel. Methods. 2023, 219: 73-81
• Xiaoqing Ru, QuanZou, Chen Lin*. Optimization of drug-target affinity prediction methodsthrough feature processing schemes. Bioinformatics. 2023, 39(11):btad615 (codes)
• Ren Qi, Quan Zou*. Editorial: MachineLearning Methods in Single-Cell Immune and Drug Response Prediction. Frontiersin Genetics. 2023, 19: 1233078
• Zhecheng Zhou, Linlin Zhuo*, Xiangzheng Fu*, Quan Zou*. JointDeep Autoencoder and Subgraph Augmentation for Inferring Microbial Responses toDrugs. Briefings in Bioinformatics. 2024, 25(1): bbad483. (codes)
• Junkai Liu, Shixuan Guan, Quan Zou, Hongjie Wu*,Prayag Tiwari, Yijie Ding. AMDGT: Attention aware multi-modal fusion using adual graph transformer for drug–disease associations prediction. Knowledge-BasedSystems. 2024, 284: 111359
• Zhecheng Zhou, Zhenya Du, Xin Jiang, Linlin Zhuo*, Yixin Xu,Xiangzheng Fu*, Mingzhe Liu, Quan Zou*. GAM-MDR: probing miRNA–drugresistance using a graph autoencoder based on random path masking. Briefingsin Functional Genomics. Doi: 10.1093/bfgp/elae005. (codes)
• Zhecheng Zhou,Qingquan Liao, Jinhang Wei, Linlin Zhuo*, Xiaonan Wu*, Xiangzheng Fu*, Quan Zou*. Revisiting Drug-Protein Interaction Prediction: A Novel Global-LocalPerspective. Bioinformatics. Doi:10.1093/bioinformatics/btae271. (codes)